P345: IN SILICO DRUG REPURPOSING STUDY AND MOLECULAR SIGNATURE IDENTIFICATION ON ADULT ACUTE LYMPHOBLASTIC LEUKEMIA
Authors: Yagmur Kiraz Durmaz, Betül Budak, Ezgi Yağmur Tükel, Beste Turanli
Journal: HemaSphere (2023)

Background: Acute lymphoblastic leukemia (ALL) is known to be a very hetereogenous disease having identified various genetic abnormalities that causes disease progression. The most commonly seen subtype of ALL is Philadelphia positive ALL (Ph+ALL) which carries BCR/ABL translocation that makes the disease high-risk and more aggressive. On top of the complicated molecular pattern of the disease, drug resistance is seen as an obstacle in the clinics. Therefore, there is a need for identifying alternative targets that would serve as better options for ALL treatment. Aims: The aim in this study is to compare the molecular profiles of ALL and Ph+ ALL by integrating data from multiple biomolecular levels. Transcriptome datasets are aimed to be analyzed to build biological networks and to identify molecular reporters together with biological processes. Also, by identifying new molecular targets, new treatment options will be suggested by using drug repurposing strategy. Methods: ALL and Ph+ ALL-associated transcriptomics datasets are analyzed statistically by using R/Bioconductor software platform. Differentially expressed genes were identified and associated with reporter molecules, receptor, transcription factor, miRNA, metabolites in addition to reconstruction of protein-protein interaction networks. Hub proteins are identified according to degree and betweenness centrality. Drug repurposing is conducted by using L1000CDS2 for the agents that can potentially reverse protein expressions in the disease. Genexpharma is used for network based drug repurposing studies that targets hub proteins. Results: As a result of this meta-analysis, we found 799 DEGs for ALL and 295 DEGs for Ph+ALL datasets. Top 3 upregulated DEGs are listed as: DNTT, CTGF and PXDN for ALL; DNTT, SOCS2 and MME for Ph+ALL which some of them are not studied before. Upon determining the DEGs for both type of ALL, other marker molecules (receptors, protein-protein interaction, transcription factors, miRNAs, metabolites) were also detected together with key genes that are located at central positions within the network were also identified. CDKN1A, HSP90AA1, PCNA, PIK3R1, SMARCA4, YWHAB, and YWHAE in ALL; LYN and RANBP9 in Ph+ALL were detected prominently as hub proteins. According to gene enrichment analysis, cell activation, immune response, hematopoietic lineage related genes were identified as significant in both ALL and Ph+ ALL datasets. A network of 123 interactions with 99 drugs that targets 13 hub proteins in ALL and 289 interactions with 203 drugs targeting 19 hub protein were build and 37 anti-neoplastic agents such as dasatinib, flurouracil, docetaxel were identified commonly in both networks. Most importantly, as a result of individual analyses for both types of ALL; methylphenidate, maytansine, isoprenaline and; citalopram, desipramine, glipizide that targets hub proteins are identifed as potential drugs that can be used in ALL and Ph+ALL respectively. Summary/Conclusion: This study is the first by having broad comparative analyses in ALL and Ph+ ALL together with serving as a pool to study the roles of each identified factor in the disease progression. The results elucidated by this project will further use in in vitro validation tests and may pave the way for novel target identification and repurposed drug applications.Keywords: Transcriptional target, Drug resistance, Microarray analysis, Acute lymphoblastic leukemia